Different perspectives.
A shared practical question.

Dr. Mariana Hebborn

AI leadership, data governance, and organizational change

Mariana connects data and AI strategy with the people, products, and responsibilities needed to put it into practice. Her career spans data science and digital transformation at IBM, Fujitsu, Viridium, and Merck, including teams and projects across Europe and Asia. At Merck, her work has developed from healthcare data governance to global leadership of HR AI and data governance. Her conference contributions explore federated governance, product thinking, and the conditions for responsible AI adoption.

Current work

Global Head of HR AI & Data Governance, Merck Group

Background

PhD in Computational Data Processing; international experience leading data science and digitalization projects

In practice

Federated data governance, data and AI product thinking, and organizational adoption

Prof. Dr. Heiko Beier

Applied research, knowledge systems, and dependable AI

Heiko connects scientific research, software entrepreneurship, and the practical use of AI. His early work in experimental particle physics at DESY and Columbia University shaped his interest in extracting meaning from complex data. He co-founded MORESOPHY in 2001 and combines its development with teaching and research at SDI München. His work spans semantic analysis, knowledge management, and hybrid AI, helping organizations make unstructured information useful in communication, service, and other knowledge-intensive processes.

Current work

Professor of Digital Media Communication and Artificial Intelligence, SDI München; co-founder and CEO, MORESOPHY

Background

Doctorate in experimental particle physics; research at DESY and Columbia University

In practice

Explainable and hybrid AI, natural language understanding, semantic data analysis, and knowledge management

Dr. Jan-Hendrik Weinert

Data & AI strategy, corporate AI platforms, and governance

Jan-Hendrik works at the intersection of data, AI, technology, governance, and risk. He focuses on turning strategic ambitions into scalable enterprise capabilities, working across Data & AI strategy, enterprise architecture, and hands-on implementation.

He has designed and built a Corporate AI & Analytics Platform that enables teams to independently develop and bring AI and analytics use cases into production within governance, security, and software engineering guardrails. His work includes modern data architectures, governed self-service capabilities, and putting Data Mesh principles into practice. He translates AI, information security, and regulatory requirements into practical technical solutions.

With a background in actuarial science, quantitative finance, and business informatics, he bridges business, risk management, and technology. His particular interests include Data & AI Strategy, Corporate AI Platforms, AI Governance, Data Architecture, Data Democratization, and the transformation of financial services through Data & AI.

Current work

Expert Risk Analytics, Viridium Group; Chief Data Officer as a Service through Holonexus

Background

PhD in Actuarial Science and master’s degrees in Business Informatics and Finance, Goethe University Frankfurt; Certified Chief Data Officer

In practice

Corporate AI & Analytics Platforms, governed self-service, Data Mesh, and technical implementation of AI, security, and regulatory requirements